Blinding and Randomization.

Most, if not all, guidelines, recommendations, and other texts on Good Research Practice emphasize the importance of blinding and randomization. There is, however, very limited specific guidance on when and how to apply blinding and randomization. This chapter aims to disambiguate these two terms by discussing what they mean, why they are applied, and how to conduct the acts of randomization and blinding. We discuss the use of blinding and randomization as the means against existing and potential risks of bias rather than a mandatory practice that is to be followed under all circumstances and at any cost. We argue that, in general, experiments should be blinded and randomized if (a) this is a confirmatory research that has a major impact on decision-making and that cannot be readily repeated (for ethical or resource-related reasons) and/or (b) no other measures can be applied to protect against existing and potential risks of bias.

The MIXED framework: A novel approach to evaluating mixed-methods rigor.

Evaluation of rigor in mixed-methods (MM) research is a persistent challenge due to the combination of inconsistent philosophical paradigms, the use of multiple research methods which require different skill sets, and the need to combine research at different points in the research process. Researchers have proposed a variety of ways to thoroughly evaluate MM research, but each method fails to provide a framework that is useful for the consumer of research. In contrast, the MIXED framework is meant to bridge the gap between an academic exercise and practical assessment of a published work. The MIXED framework (methods, inference, expertise, evaluation, and design) borrows from previously published frameworks to create a useful tool for the evaluation of a published study. The MIXED framework uses an experimental eight-item scale that allows for comprehensive integrated assessment of MM rigor in published manuscripts. Mixed methods are becoming increasingly prevalent in nursing and healthcare research requiring researchers and consumers to address issues unique to MM such as evaluation of rigor.

Operationalizing reflexivity to improve the rigor of palliative care research.

Reflective practice involves deliberate consideration of actions, attitudes and behaviors. Reflexivity in research is considered important for ensuring that research is ethically and rigorously conducted. This paper details the challenges of conducting research involving patients with palliative care needs within the acute hospital environment. It discusses the contribution of reflexivity to a pilot study using the Patient Dignity Question (PDQ) "What do I need to know about you as a person to take the best care of you that I can?" as a brief intervention to foster a more person-centered climate. Challenges that emerged are discussed from the perspectives of the researchers, the participants, and the setting; they relate to: timing and recruitment, the nature of palliative care illness, attitudes to research, and the research environment. Awareness of such issues can prompt researchers to devise appropriate strategies and approaches that may inform and assist the rigor and conduct of future research.

Charting a Course: Navigating Rigor and Meaning in Global Health Research.

In the rapidly evolving landscape of global health research, the tension between scientific rigor and contextual meaning presents a critical challenge. Drawing on our work with the Global Diet and Physical Activity Network, this commentary explores the complexities of conducting environmental audits for physical activity and diet in 4 rapidly urbanizing African cities: Yaoundé, Lagos, Cape Town, and Soweto. We illustrate the competing demands and tensions that researchers face in balancing rigor and meaning. We discuss the adaptation of internationally validated audit tools to local contexts and the importance of area-level deprivation in interpreting data. We also examine the feasibility of virtual assessment tools, emphasizing the value of local expertise. We argue for a balanced approach that marries research rigor with contextual meaning, advocating for transparency, humility, and meaningful community engagement.

Back to the Future of Neuropsychopharmacology.

Disappointments in translating preclinical findings into clinical efficacy have triggered a number of changes in neuroscience drug discovery ranging from investments diverted to other therapeutic areas to reduced reliance on efficacy claims derived from preclinical models. In this chapter, we argue that there are several existing examples that teach us on what needs to be done to improve the success rate. We advocate the reverse engineering approach that shifts the focus from preclinical efforts to "model" human disease states to pharmacodynamic activity as a common denominator in the journey to translate clinically validated phenomena to preclinical level and then back to humans. Combined with the research rigor, openness, and transparency, this reverse engineering approach is well set to bring new effective and safe medications to patients in need.

Introduction to the EQIPD quality system.

While high risk of failure is an inherent part of developing innovative therapies, it can be reduced by adherence to evidence-based rigorous research practices. Supported through the European Union's Innovative Medicines Initiative, the EQIPD consortium has developed a novel preclinical research quality system that can be applied in both public and private sectors and is free for anyone to use. The EQIPD Quality System was designed to be suited to boost innovation by ensuring the generation of robust and reliable preclinical data while being lean, effective and not becoming a burden that could negatively impact the freedom to explore scientific questions. EQIPD defines research quality as the extent to which research data are fit for their intended use. Fitness, in this context, is defined by the stakeholders, who are the scientists directly involved in the research, but also their funders, sponsors, publishers, research tool manufacturers, and collaboration partners such as peers in a multi-site research project. The essence of the EQIPD Quality System is the set of 18 core requirements that can be addressed flexibly, according to user-specific needs and following a user-defined trajectory. The EQIPD Quality System proposes guidance on expectations for quality-related measures, defines criteria for adequate processes (i.e. performance standards) and provides examples of how such measures can be developed and implemented. However, it does not prescribe any pre-determined solutions. EQIPD has also developed tools (for optional use) to support users in implementing the system and assessment services for those research units that successfully implement the quality system and seek formal accreditation. Building upon the feedback from users and continuous improvement, a sustainable EQIPD Quality System will ultimately serve the entire community of scientists conducting non-regulated preclinical research, by helping them generate reliable data that are fit for their intended use.

Evidence of misuse of nonparametric tests in the presence of heteroscedasticity within obesity research.

BACKGROUND: Classic nonparametric tests (cNPTs), like Kruskal-Wallis or Mann-Whitney U, are sometimes used to detect differences in central tendency ( i.e., means or medians). However, when the tests' assumptions are violated, such as in the presence of unequal variance and other forms of heteroscedasticity, they are no longer valid for testing differences in central tendency. Yet, sometimes researchers erroneously use cNPTs to account for heteroscedasticity. OBJECTIVE: To document the appropriateness of cNPT use in obesity literature, characterize studies that use cNPTs, and evaluate the citation and public sharing patterns of these articles. METHODS: We reviewed obesity studies published in 2017 to determine whether the authors used cNPTs: (1) to correct for heteroscedasticity (invalid); (2) when heteroscedasticity was clearly not present (correct); or (3) when it was unclear whether heteroscedasticity was present (unclear). Open science R packages were used to transparently search literature and extract data on how often papers with errors have been cited in academic literature, read in Mendeley, and disseminated in the media. RESULTS: We identified nine studies that used a cNPT in the presence of heteroscedasticity (some because of the mistaken rationale that the test corrected for heteroscedasticity), 25 articles that did not explicitly state whether heteroscedasticity was present when a cNPT was used, and only four articles that appropriately reported that heteroscedasticity was not present when a cNPT was used. Errors were found in observational and interventional studies, in human and rodent studies, and only when studies were unregistered. Studies with errors have been cited 113 times, read in Mendeley 123 times, and disseminated in the media 41 times, by the public, scientists, science communicators, and doctors. CONCLUSIONS: Examples of inappropriate use of cNPTs exist in the obesity literature, and those articles perpetuate the errors via various audiences and dissemination platforms.

Persistent confusion in nutrition and obesity research about the validity of classic nonparametric tests in the presence of heteroscedasticity: evidence of the problem and valid alternatives.

The use of classic nonparametric tests (cNPTs), such as the Kruskal-Wallis and Mann-Whitney U tests, in the presence of unequal variance for between-group comparisons of means and medians may lead to marked increases in the rate of falsely rejecting null hypotheses and decreases in statistical power. Yet, this practice remains prevalent in the scientific literature, including nutrition and obesity literature. Some nutrition and obesity studies use a cNPT in the presence of unequal variance (i.e., heteroscedasticity), sometimes because of the mistaken rationale that the test corrects for heteroscedasticity. Herein, we discuss misconceptions of using cNPTs in the presence of heteroscedasticity. We then discuss assumptions, purposes, and limitations of 3 common tests used to test for mean differences between multiple groups, including 2 parametric tests: Fisher's ANOVA and Welch's ANOVA; and 1 cNPT: the Kruskal-Wallis test. To document the impact of heteroscedasticity on the validity of these tests under conditions similar to those used in nutrition and obesity research, we conducted simple simulations and assessed type I error rates (i.e., false positives, defined as incorrectly rejecting the null hypothesis). We demonstrate that type I error rates for Fisher's ANOVA, which does not account for heteroscedasticity, and Kruskal-Wallis, which tests for differences in distributions rather than means, deviated from the expected significance level. Greater deviation from the expected type I error rate was observed as the heterogeneity increased, especially in the presence of an imbalanced sample size. We provide brief tutorial guidance for authors, editors, and reviewers to identify appropriate statistical tests when test assumptions are violated, with a particular focus on cNPTs.

Immigrants as Research Partners: A Review of Immigrants in Community-Based Participatory Research (CBPR).

Community-based participatory research (CBPR) is uniquely suited to engage immigrants in all aspects of research, from research question development to data collection to interpretation and dissemination of results. An increasing number of research studies have utilized the methodology for exploring complex health issues for immigrants. In the current manuscript, we present a review of peer-reviewed articles in health-related research where CBPR was conducted in partnership with immigrants. We examined the role of immigrants in the CBPR process and how immigrant involvement improved/enhanced the research rigor. A total of 161 articles met the inclusion criteria. The results of this literature review enhance our understanding of how CBPR can be used in direct collaboration with immigrants and highlights the many potential benefits for both researchers and immigrant communities.